Article

A Big Bang model of human colorectal tumor growth

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Abstract

What happens in early, still undetectable human malignancies is unknown because direct observations are impractical. Here we present and validate a 'Big Bang' model, whereby tumors grow predominantly as a single expansion producing numerous intermixed subclones that are not subject to stringent selection and where both public (clonal) and most detectable private (subclonal) alterations arise early during growth. Genomic profiling of 349 individual glands from 15 colorectal tumors showed an absence of selective sweeps, uniformly high intratumoral heterogeneity (ITH) and subclone mixing in distant regions, as postulated by our model. We also verified the prediction that most detectable ITH originates from early private alterations and not from later clonal expansions, thus exposing the profile of the primordial tumor. Moreover, some tumors appear 'born to be bad', with subclone mixing indicative of early malignant potential. This new model provides a quantitative framework to interpret tumor growth dynamics and the origins of ITH, with important clinical implications.

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Acknowledgements

The authors would like to acknowledge the technical assistance of R. Guzman. This project was supported in part by an award to C.C. from the V Foundation for Cancer Research and by award numbers P30CA014089, R21CA149990 and R21CA151139 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the US National Institutes of Health. M.F.P. was supported by a grant from the California Institute for Regenerative Medicine (CIRM).

Author information

Author notes

    • Andrea Sottoriva
    • , Zhicheng Ma
    •  & Christina Curtis

    Present addresses: Division of Molecular Pathology, The Institute of Cancer Research, London, UK (A.S.), Department of Medicine, Stanford University, Stanford, California, USA (Z.M. and C.C.) and Department of Genetics, Stanford University, Stanford, California, USA (Z.M. and C.C.).

Affiliations

  1. Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA.

    • Andrea Sottoriva
    • , Zhicheng Ma
    • , Matthew P Salomon
    • , Junsong Zhao
    • , Paul Marjoram
    • , Kimberly Siegmund
    •  & Christina Curtis
  2. Department of Pathology, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA.

    • Haeyoun Kang
    • , Michael F Press
    •  & Darryl Shibata
  3. Department of Pathology, CHA University, Seongnam-si, South Korea.

    • Haeyoun Kang
  4. Center for Evolution and Cancer, University of California, San Francisco, San Francisco, California, USA.

    • Trevor A Graham
  5. Centre for Tumor Biology, Barts Cancer Institute, Queen Mary University of London, London, UK.

    • Trevor A Graham

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Contributions

A.S., D.S. and C.C. designed the study, interpreted the data and constructed the model. D.S. provided clinical specimens. Z.M. and D.S. processed the specimens. Z.M. generated sequencing data. P.M. and K.S. contributed data. H.K. and M.F.P. performed FISH. A.S. developed and implemented the computational framework. A.S., M.P.S. and J.Z. analyzed the data with oversight from C.C. A.S., D.S. and C.C. wrote the manuscript with input from T.A.G. D.S. and C.C. oversaw the study. All authors read and approved the final manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Darryl Shibata or Christina Curtis.

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